🙌 Get a free 1-year Subscription
Purchase your second Modal course and we'll set you up with a free 1-year subscription. Learn More.
Classify Data and Make Predictions: KNN and SVM
When
June 6, 2024 - July 21, 2024
Course Tuition
$1,950
No Up-front Payment
Modal now offers a deferred direct bill payment option for Booz Allen employees.
Learn more
Learn more
Who Is This For?
Data Professionals interested in building on their foundational supervised ML knowledge by learning new models for classifying data and making predictions.
Any prerequisites?
Machine Learning
• Knowledge of linear and logistic regression and basic principles of machine learning.
• Familiarity with supervised learning algorithms.
• Identifying regression vs. classification ML problems.
• Model evaluation methods including train/test split and statistics such as mean absolute error, accuracy, precision, recall, and F1 score.
• The concept of overfitting and underfitting.
Python
• Strong familiarity with Python, including data structures, loops, functions, code debugging, and reading error messages.
• Experience with data manipulation using the Pandas library.
What will I be able to do after this Course?
By the end of the course, you’ll know how to train, test, and tune KNN and SVM models to solve classification and prediction problems, and reliably choose the right algorithm for the job.
NEED HELP DECIDING?
Book time with a learning expert.
A Typical Week
Monday
Self Study
Kick-off new topic with self-study & online learning
- Coaches support learners hitting roadblocks
- Manager check-in to bring learning into company context
Tuesday
Wednesday
Labs
Learning material leads into practice environment & labs
- Coaches support learners hitting roadblocks
- Pair programming to bring learning into company context
- Community allows students to help each other
Thursday
Live Event
Interactive live session hosted by Coaches
- Community allows students to help each other
- Community Groups host expert AMAs & guided community discussions
Friday
Projects
Work on a weekly project
- Community allows students to help each other
- Group projects
- Coaches support learners hitting roadblocks
Saturday
sunday
Work at your own pace
Expert coaching and actionable feedback from Coaches
.svg)
Course Schedule
Sprint 1: K-Nearest Neighbors
Learn how to implement an ML pipeline using a k-nearest neighbors model and understand the key concepts behind the KNN algorithm. You then apply what you’ve learned to help a bank identify and reach out to customers that are likely to cancel their credit cards.
Sprint 2: Support Vector Machines
Learn how to implement a machine learning pipeline using a Support Vector Machine model and understand the key components of an SVM. You’ll apply what you’ve learned by trying a new approach to helping the bank identify customers that are likely to cancel their credit cards and comparing the results.
Sprint 3: Comparing Models and Making Predictions
Learn about the strengths and weaknesses of KNN and SVM models and compare their performance. You’ll apply what you’ve learned by helping the bank run a promotional campaign, identifying current at risk customers and writing a summary of how they differ from the average customer.
Why Modal?
.svg)
Projects & Practice
Real world exercises contextualize learning in real-world context.
On-Demand Coach Support
You are never alone. Coaches are always present and can help you!
Live Sessions
Hear from guest speakers and expert instructors through engaging lectures.
Technical Labs
Hands-on labs allow you to play with new tools and concepts to build real skills.
Community of Peers
You will be part of a learning community were support is abundant.
Asynchronous Learning
Self-paced learning is scheduled for each learner, with a dashboard to help you keep on track.
Other Courses
“I love the quantity & quality of learning materials, the interactivity, the live sessions, the coaches, are invaluable. I can really feel the difference in the level of engagement that Modal has to every participant compared to an ordinary course."
.svg)
- Veselina Stoyanova - Reporting Analyst, EMAG
Learn more about FlexEd
We are excited that Modal now offers a deferred direct bill payment option for Booz Allen employees.
The deferred direct bill payment option enables employees to enroll in learning opportunities with no upfront costs. This payment option will require the employee to sign a Family Educational Rights and Privacy Act (FERPA) agreement with Modal to release grades/completion to Booz Allen to satisfy the FlexEd Program completion requirement.
Note, Modal may also be used for the FlexEd Program reimbursement payment option. See the full FlexEd Program Policy & FAQs.
Learn more about FlexEdThe deferred direct bill payment option enables employees to enroll in learning opportunities with no upfront costs. This payment option will require the employee to sign a Family Educational Rights and Privacy Act (FERPA) agreement with Modal to release grades/completion to Booz Allen to satisfy the FlexEd Program completion requirement.
Note, Modal may also be used for the FlexEd Program reimbursement payment option. See the full FlexEd Program Policy & FAQs.
Need help? Contact us